Decision analysis for sustainable development: The case of renewable energy planning under uncertainty

Multi-Criteria Decision Analysis (MCDA) methods are increasingly used to aid decision-making for sustainable development. However, although uncertainty is present in all decision environments, dealing with incomplete and vague information in decision analysis remains a challenge. Our objective is to simplify the incorporation of uncertainty in the scoring of alternatives in MCDA processes. We present a modified ELimination and Choice Translating REality (ELECTRE) III model, in which the uncertainty in the performance scores is expressed as lower/upper bounds and then added to the model's discrimination thresholds. Unlike other uncertainty approaches developed in the literature (such as those based on fuzzy set theory), our approach does not require additional knowledge apart from understanding the ELECTRE III model. To test its validity and suitability, we apply it for the evaluation of renewable energy resources for Turkey - hydro, wind, geothermal, solar, and biomass - under five main criteria: technological, technical, economic, environmental, and socio-politic. Our results indicate that wind energy is the best alternative for Turkey, followed by solar energy, which is in line with country's Vision 2023 energy targets. (c) 2020 Elsevier B.V. All rights reserved.

Automated summary

This study aims to simplify the incorporation of uncertainty in the scoring of alternatives in Multi-Criteria Decision Analysis processes. The authors present a modified ELECTRE III model and apply it to evaluate renewable energy resources for Turkey, with wind energy identified as the best alternative followed by solar energy.